Universal Polar Code Construction for Mixed Channel Reliability
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Solution Overview
Problem
Next-generation wireless communication networks, such as 5G and New Radio (NR), require improved error correction codes that can perform well across various channel conditions, including Additive White Gaussian Noise (AWGN) and fading channels, while also supporting a wide range of code rates, which existing polar codes struggle to achieve.
Innovation Solution
The construction of robust and universal polar codes is achieved by sorting synthetic channels based on a convex combination of mutual information calculated for AWGN and binary erasure channels, or using cumulative sums to determine channel reliability, allowing for the identification of the best channels to transmit information bits and frozen bits, thereby enhancing coding performance across different channel conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional polar codes are designed for specific channel conditions (AWGN or fading), then they achieve good error correction performance for those specific conditions, but they fail to maintain robust performance across diverse channel conditions and code rates
Solution Approach 1:
The patent creates a universal polar code construction method that works across different channel conditions (AWGN and fading channels) and various code rates. By using a convex combination of mutual information from both channel models, the code design achieves SNR-independence and universal applicability, allowing the same code construction to perform reliably regardless of the specific channel conditions or code rate requirements.
Solution Approach 2:
The patent changes the parameter used for channel sorting from traditional single-channel mutual information to a convex combination of mutual information from two different channel models (AWGN and binary erasure channels). This parameter transformation enables the code to adapt to varying channel conditions by incorporating characteristics from both AWGN and fading channel models, achieving robust performance across diverse scenarios.
2Adaptability or versatility
If polar codes are optimized for wide range of code rates, then they support diverse communication requirements, but existing methods incur storage penalties and lose SNR-independence
Solution Approach 1:
The patent develops a universal code construction method that simultaneously supports a wide range of code rates while maintaining SNR-independence. By using the convex combination approach for channel sorting, the same construction methodology can be applied across different code rates without requiring separate optimized codes, thereby avoiding storage penalties and preserving the SNR-independent property.
3Productivity
If synthetic channels are sorted using traditional mutual information methods, then the sorting is simple and fast, but the resulting polar codes do not achieve optimal performance across different channel types
Solution Approach 1:
The patent merges the mutual information calculations from two different channel models (AWGN and binary erasure channels) into a convex combination. This combination approach integrates the strengths of both models, enabling the sorted synthetic channels to reflect characteristics of both AWGN and fading channels, thereby achieving optimal performance across diverse channel types while maintaining a relatively simple sorting process.
Data Source
AI summary
Aspects of the disclosure relate to polar coding. A polar codeword may be generated by sorting a plurality of synthetic channels utilized for transmission of the polar codeword over an air interface in order of reliability utilizing a convex combination of the mutual information calculated for each synthetic channel based on an Additive White Gaussian Noise (AWGN) channel and the mutual information calculated for each synthetic channel based on a binary erasure channel. A polar codeword may further be generated by sorting the plurality of synthetic channels in order of reliability utilizing cumulative sums calculated for each synthetic channel. Each cumulative sum may be calculated from a binary representation of a position of the synthetic channel within the plurality of synthetic channels.